code: def test_batch(self):
      a = torch.tensor([[4, 2, 8], [1, 2, 3]], dtype=torch.float).view(
          2, 3, 1
      )
      b = torch.tensor([[0, 2], [-1, 2]], dtype=torch.float).view(
          2, 2, 1
      )
      period = torch.tensor(1, dtype=torch.float).view(1, 1, 1)
      lengthscale = torch.tensor(2, dtype=torch.float).view(1, 1, 1)
      kernel = PeriodicKernel().initialize(
          lengthscale=lengthscale, period_length=period
      )
      kernel.eval()
  
      actual = torch.zeros(2, 3, 2)
      for k in range(2):
          actual[k] = kernel(a[k], b[k]).to_dense()
  
      res = kernel(a, b).to_dense()
      self.assertLess(torch.norm(res - actual), 1e-5)
  
file_path: gpytorch/test/kernels/test_periodic_kernel.py
imports: import math
  import unittest
  import torch
  from gpytorch.kernels import PeriodicKernel
  from gpytorch.priors import NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 6 for calling the TestPeriodicKernel obj's underlying member method code with example usage: obj.test_batch() without return types